IoT Case StudySealed Air Corporation

Sealed Air is a global manufacturer of protective and speciality packaging for food and consumer good as well as cleaning and hygiene solutions known for brands like Bubble wrap, Cryovac and Diversey Care cleaning and hygiene.

Their Objectivescleaning and hygiene. Sealed Air wanted to improve some of their products as their customers wanted to increase energy e ciency and compliance. To do this, they needed new insights for their products. They decided to start with the SoftCare Line soap and sanitizer dispenser.

The SolutionJoining with Sealed Air, D6 Labs, and Dash Replenishment Service, ThingLogix provided insight-driven IoT services for their SoftCare line of soap dispensers in order to create new business value.

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SoftCare Line soap dispenser:

The soap dispenser reports “pumps”. Based on these insights, customers who outfit their facilities with several dispenser receive lots of useful information. Insights they received from “pump” count:

1. Custodial crews know when a soap dispenser is getting low on soap (approximately 800 pumps), instead of manually inspecting.

2. Custodial crews know the foot tra c for particular restrooms. Servicing restrooms based on specific use vs. scheduling or manually inspection.

3. Customers in the food industry (restaurants, grocery stores) improve employee hygiene compliance by knowing how much soap/sanitizer is being used by employees.

4. When dispensers jointly reach a number of ‘pumps’, a new order of soap can be made to restock a facility’s inventory, eliminating human involvement and reducing man-hours.

We first strategized with Sealed Air to understand and then implement the most efficient way of reaching these new objectives. By understanding their desired ROI, we built a scalable service on top of Amazon Web Services, utilizing AWS IoT, Lambda, DynamoDB, Elastic Beanstalk, EC2, RDS, and Elastic Search. Sealed Air used ThingLogix Foundry to design, deploy, and manage every dispenser in the field. We then made sure that the new data coming from these products were built into their process. The time-to market was under three months.